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Reason for revert: There are many statsd servers exist: - https://github.com/statsd/statsd - classical statsd server - https://docs.datadoghq.com/developers/dogstatsd/ - statsd server from DataDog built into DatDog Agent ( https://docs.datadoghq.com/agent/ ) - https://github.com/avito-tech/bioyino - high-performance statsd server - https://github.com/atlassian/gostatsd - statsd server in Go - https://github.com/prometheus/statsd_exporter - statsd server, which exposes the aggregated data as Prometheus metrics These servers can be used for efficient aggregating of statsd data and sending it to VictoriaMetrics according to https://docs.victoriametrics.com/#how-to-send-data-from-graphite-compatible-agents-such-as-statsd ( the https://github.com/prometheus/statsd_exporter can be scraped as usual Prometheus target according to https://docs.victoriametrics.com/#how-to-scrape-prometheus-exporters-such-as-node-exporter ). Adding support for statsd data ingestion protocol into VictoriaMetrics makes sense only if it provides significant advantages over the existing statsd servers, while has no significant drawbacks comparing to existing statsd servers. The main advantage of statsd server built into VictoriaMetrics and vmagent - getting rid of additional statsd server. The main drawback is non-trivial and inconvenient streaming aggregation configs, which must be used for the ingested statsd metrics ( see https://docs.victoriametrics.com/stream-aggregation/ ). These configs are incompatible with the configs for standalone statsd servers. So you need to manually translate configs of the used statsd server to stream aggregation configs when migrating from standalone statsd server to statsd server built into VictoriaMetrics (or vmagent). Another important drawback is that it is very easy to shoot yourself in the foot when using built-in statsd server with the -statsd.disableAggregationEnforcement command-line flag or with improperly configured streaming aggregation. In this case the ingested statsd metrics will be stored to VictoriaMetrics as is without any aggregation. This may result in high CPU usage during data ingestion, high disk space usage for storing all the unaggregated statsd metrics and high CPU usage during querying, since all the unaggregated metrics must be read, unpacked and processed during querying. P.S. Built-in statsd server can be added to VictoriaMetrics and vmagent after figuring out more ergonomic specialized configuration for aggregating of statsd metrics. The main requirements for this configuration: - easy to write, read and update (ideally it should work out of the box for most cases without additional configuration) - hard to misconfigure (e.g. hard to shoot yourself in the foot) It would be great if this configuration will be compatible with the configuration of the most widely used statsd server. In the mean time it is recommended continue using external statsd server. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6265 Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5053 Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5052 Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/206 Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4600 |
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| .. | ||
| common | ||
| csvimport | ||
| datadogsketches | ||
| datadogv1 | ||
| datadogv2 | ||
| graphite | ||
| influx | ||
| native | ||
| newrelic | ||
| opentelemetry | ||
| opentsdb | ||
| opentsdbhttp | ||
| prometheusimport | ||
| prompush | ||
| promremotewrite | ||
| relabel | ||
| static/css | ||
| vmimport | ||
| main.go | ||
| README.md | ||
vminsert routes the ingested data to vmstorage.